1st Grade Science Quiz: Which Design Works Better

20 questions · exam conditions

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Which Design Works BetterQuestion 1 of 20

Marcus and Yuki tested two bases to keep a tower from tipping. Design A has a narrow base and it tipped (yes). Design B has a wide base and it stayed up (yes). A tried to help, but tipping was a weakness. B was strong because the wide base stayed stable. They need the best base for a steady tower. Design B works better than Design A because the data shows it did not tip. The wide base keeps it steady, solving the stability problem. Based on the data, what does the data tell us about which design solves the problem better?

Design A works better because it tipped, so it is more stable.

Design B works better because it stayed up, so the wide base stops tipping.

Design B works better because it is bigger and looks strong.

Design B works better because it stayed up.

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1st Grade Science Quiz

1st Grade Science Quiz: Which Design Works Better

Practice Which Design Works Better in 1st Grade Science with focused quiz questions that help you check what you know, review explanations, and build confidence with test-style prompts.

What this quiz covers

This quiz focuses on Which Design Works Better, giving you a quick way to practice the rules, question types, and explanations that matter most for 1st Grade Science.

How to use this quiz

Try each quiz question before looking at the correct answer. Use the explanations to review missed ideas, then come back to similar questions until the pattern feels familiar.

All questions

Question 1

Design A works better because it tipped, so it is more stable.
Design B works better because it stayed up, so the wide base stops tipping. (correct answer)
Design B works better because it is bigger and looks strong.
Design B works better because it stayed up.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, [problem: preventing container from tipping]. Test data showed: Design A [results: tipped over (yes)]. Design B [results: stayed standing (yes)]. The students concluded that Design [B] works better because [specific reasoning from stimulus: the data shows it didn't tip over, proving the wide base provides stability]. Choice [B] is correct because it [identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion]. For example, [specific complete reasoning: 'Design B works better because the data shows it stayed up (evidence), which means the wide base (design feature) prevents tipping (solves problem)']. Choice [A] represents [error type: reversed logic]. This error typically occurs when students [developmental explanation: confuse designs' results]. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 2

During design review time, Sofia and Chen tested two containers to organize supplies. Design A was one big box, and the items got mixed up (yes). Design B had dividers, and the items stayed separated (yes). Both designs tried to solve the same organization problem. Design B's strength is dividers keep things apart, and Design A's weakness is items mix together. Chen pointed to the results and said, "Separated helps us find things fast." Sofia said, "Let's choose using evidence, not guessing." Their teacher asked, "Which design should we choose and why?" Based on the test results, which container design should they choose and why?

Design A works better because the data shows items mixed up, so it organizes supplies well.
Design B works better because the data shows items stayed separated, so the dividers stopped mixing. (correct answer)
Design B works better because it looks nicer than Design A.
Design B works better because it stayed separated, but that does not help organizing.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem is organizing supplies without mixing. Test data showed: Design A results: items got mixed (yes). Design B results: items stayed separated (yes). The students concluded that Design B works better because the data shows items stayed separated, proving the dividers prevent supplies from mixing. Choice B is correct because it identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion. For example, 'Design B is better because test results show items stayed separated (evidence), proving the dividers (design feature) prevent supplies from getting mixed up (solves problem)'. Choice C represents aesthetic reasoning. This error typically occurs when students focus on non-functional aspects like appearance or ease of building. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 3

At design review time, Sofia and Amir tested two trays for carrying books. Design A was flat, and 2 books fell off. Design B had raised edges, and 0 books fell off. Both designs tried to solve the carrying problem, but the data shows a difference. Design B's strength is the edges help stop sliding, and Design A's weakness is no edges. Amir said, "We should use evidence from the test." Sofia pointed to the number 0 and smiled. The teacher asked, "Why does one design work better than the other?" Why does Design B work better than Design A?

Design B works better because the data shows 0 books fell, so the edges stopped books from sliding off. (correct answer)
Design A works better because the data shows 2 books fell, so it must be safer.
Design B works better because it is newer and more fun.
Design B works better because it has edges, but the data does not matter.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem is carrying books without dropping. Test data showed: Design A results: 2 books fell. Design B results: 0 books fell. The students concluded that Design B works better because the data shows 0 books fell, proving the raised edges successfully prevented books from sliding off. Choice A is correct because it identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion. For example, 'Design B works better because the data shows 0 books fell (evidence), which means the raised edges (design feature) successfully prevented books from sliding off when carrying them (solves problem)'. Choice B represents reversed logic. This error typically occurs when students confusing designs' results. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 4

In the classroom, Emma and Chen tested two shelves to store books. Design A had 1 shelf and held 8 books. Design B had 3 shelves and held 24 books. Both designs tried to solve the storage problem, but one held more. Design B's strength is more shelves give more space, and Design A's weakness is it has less room. Chen said, "The data shows B holds a lot more books." Emma wrote the numbers on the board. The teacher asked, "Which should we choose, and what evidence tells you?" Based on the data, which shelf design best solves the problem and why?

Design B works better because the data shows 24 books, so more shelves make more storage space. (correct answer)
Design A works better because it held 8 books, so it holds more than 24.
Design B works better because it is taller, and tall things are better.
Design B works better because it held 24 books, but that is not about storage.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem is storing more books. Test data showed: Design A results: held 8 books. Design B results: held 24 books. The students concluded that Design B works better because the data shows it held 16 more books (24 vs 8), proving multiple shelves increase storage capacity. Choice A is correct because it identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion. For example, 'Design B works better because the data shows it held 24 books (evidence), proving multiple shelves (design feature) increase storage capacity (solves problem)'. Choice B represents reversed logic. This error typically occurs when students use wrong numbers. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 5

Emma and Chen tested funnels to pour juice without spilling. Design A has a wide top and spilled 2 tablespoons. Design B has a narrow top and spilled 5 tablespoons. A was strong because it caught more juice. B was weak because more juice missed the cup. They want the funnel that solves the spilling problem best. Design A works better than Design B because the data shows 2 spilled, not 5. The wide top catches more juice, so less spills out. From the evidence, which design works better?

Design B works better because the data shows it spilled 2 tablespoons.
Design A works better because the data shows 2 spilled, so the wide top catches more. (correct answer)
Design A works better because I like wide funnels.
Design A works better because it spilled 2 tablespoons.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, [problem: pouring without spilling]. Test data showed: Design A [results: spilled 2 tablespoons]. Design B [results: spilled 5 tablespoons]. The students concluded that Design [A] works better because [specific reasoning from stimulus: the data shows it spilled 3 tablespoons less (2 vs 5), proving the wide opening catches liquid better]. Choice [B] is correct because it [identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion]. For example, [specific complete reasoning: 'Design A works better because it spilled 3 tablespoons less (evidence), showing the wide opening (design feature) catches liquid better when pouring into bottles (solves problem)']. Choice [A] represents [error type: confusing designs' results]. This error typically occurs when students [developmental explanation: confuse designs' results]. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 6

Emma and Marcus tested funnels to pour juice without spilling. Funnel Design A had a wide opening, and Design B had a narrow opening. The data shows A spilled 2 tablespoons and B spilled 5 tablespoons. A was strong because it caught more juice. B was weak because more juice missed and spilled out. Marcus said, "I thought narrow would be better," but Emma showed the numbers. They want to choose the funnel that solves the pouring problem best. Based on the data, which design should they choose and why?

Design B works better because the data shows 5 tablespoons spilled, so the narrow opening catches more.
Design A works better because the data shows 2 tablespoons spilled, so the wide opening catches more juice. (correct answer)
Design A works better because I like wide funnels best.
Design A works better because it spilled less, but that does not matter for pouring.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem was pouring without spilling. Test data showed: Design A (wide funnel) spilled 2 tablespoons. Design B (narrow funnel) spilled 5 tablespoons. The students concluded that Design A works better because the data shows it spilled 3 tablespoons less (2 vs 5), proving the wide opening catches liquid better. Choice B is correct because it identifies the correct design based on data (Design A with better performance), provides evidence (cites specific test results of 2 tablespoons spilled), explains reasoning (connects data to design feature of wide opening to problem solution of catching juice), and makes a complete argument including all three parts of an evidence-based conclusion. For example, 'Design A works better because the data shows 2 tablespoons spilled (evidence), so the wide opening (design feature) catches more juice when pouring into bottles (solves problem)'. Choice D represents the error of evidence without connection. This error typically occurs when students mention the correct data but then claim it doesn't matter for the problem, not understanding that less spilling is exactly what solves the pouring problem - they have the evidence but don't connect it properly. To help students make evidence-based conclusions: Use three-part frame: 'Design A works better because 2 tablespoons spilled shows that the wide opening catches more juice'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like wide funnels best') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 7

Maya and Chen tested trays to carry books to the reading rug. Design A was flat, and Design B had raised edges. The data shows 2 books fell from A and 0 books fell from B. A tried to solve the carrying problem, but it was weak without edges. B was strong because edges helped hold books in place. Chen said, "I thought A was fine," but Maya showed the results. They want the tray that keeps books from falling. From the evidence, why does Design B work better than Design A?

Design B works better because the data shows 0 books fell, so the edges stopped books from sliding off. (correct answer)
Design B works better because the data shows 2 books fell, so edges make books fall.
Design B works better because it is new, so it must be best.
Design B works better because it has edges.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem was carrying books without dropping them. Test data showed: Design A (flat tray) had 2 books fall. Design B (tray with edges) had 0 books fall. The students concluded that Design B works better because the data shows 0 books fell, proving the raised edges successfully prevented books from sliding off. Choice A is correct because it identifies the correct design based on data (Design B with better performance), provides evidence (cites specific test results of 0 books falling), explains reasoning (connects data to design feature of edges to problem solution of preventing books from sliding), and makes a complete argument including all three parts of an evidence-based conclusion. For example, 'Design B works better because the data shows 0 books fell (evidence), so the edges (design feature) stopped books from sliding off when carrying them (solves problem)'. Choice D represents the error of correct design without complete reasoning. This error typically occurs when students identify the right design and mention a feature but don't connect the data to why that feature solves the problem, providing incomplete reasoning that's missing key connections. To help students make evidence-based conclusions: Use three-part frame: 'Design B works better because 0 books fell shows that edges keep books from sliding off'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('it is new') and evidence-based conclusion ('B works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 8

In science discussion, Amir and Maya built two step platforms to reach a high shelf. Design A was 3 inches tall, and they reached 48 inches. Design B was 6 inches tall, and they reached 51 inches. Both platforms tried to solve the reaching problem, but one helped more. Design B's strength is it gives more height, and Design A's weakness is it is shorter. Maya said, "The numbers show which one helps us reach higher." Amir checked the data again and nodded. Their teacher asked, "What does the data tell us about which design solves the problem better?" Based on the data, which platform design works better and why?

Design A works better because 48 inches is higher than 51 inches.
Design B works better because the data shows 51 inches, so the taller platform helped reach higher. (correct answer)
Design B works better because I would rather stand on it.
Design A works better because both designs reached the same height.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem is reaching high shelves. Test data showed: Design A results: reached 48 inches. Design B results: reached 51 inches. The students concluded that Design B works better because the data shows it reached 3 inches higher (51 vs 48), proving extra height helps reach higher shelves. Choice B is correct because it identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion. For example, 'Design B works better because the data shows it reached 51 inches (evidence), which means the taller platform (design feature) helped reach higher shelves (solves problem)'. Choice A represents reversed logic. This error typically occurs when students use wrong numbers. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 9

Keisha and Chen tested bases to keep a block statue standing. Design A has a narrow base and it tipped (yes). Design B has a wide base and it stayed up (yes). A tried to stand, but tipping was a weakness. B was strong because it stayed stable. They must pick the base that solves the tipping problem. Design B works better than Design A because the data shows it stayed up. The wide base keeps it from tipping, so it stands safely. Using the test results, which design should they choose and why?

Design A works better because it tipped, so it will not fall.
Design B works better because it stayed up, so the wide base stops tipping. (correct answer)
Design B works better because it is wide and looks cool.
Design B works better because it stayed up.

Question 10

Carlos and Keisha tested shelves to store classroom books. Design A has 1 shelf and holds 8 books. Design B has 3 shelves and holds 24 books. A helps some, but it is weak because it holds fewer books. B is strong because it holds many more books. They want the shelf that solves the storage problem best. Design B works better than Design A because the data shows 24 books, not 8. More shelves make more space, so it stores books better. Based on the test results, which design best solves the problem?

Design B works better because the data shows 24 books, so more shelves store more. (correct answer)
Design A works better because 8 is more than 24.
Design B works better because it has three shelves.
Design A works better because I like one shelf.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, [problem: storing more books]. Test data showed: Design A [results: held 8 books]. Design B [results: held 24 books]. The students concluded that Design [B] works better because [specific reasoning from stimulus: the data shows it held 16 more books (24 vs 8), proving multiple shelves increase storage capacity]. Choice [A] is correct because it [identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion]. For example, [specific complete reasoning: 'Design B works better because the data shows 24 books (evidence), which means the multiple shelves (design feature) allow storing more books (solves problem)']. Choice [B] represents [error type: wrong evidence]. This error typically occurs when students [developmental explanation: use wrong numbers]. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 11

Yuki and Amir tested platforms to help reach a poster. Design A is 3 inches tall and they reached 48 inches. Design B is 6 inches tall and they reached 51 inches. A was weak because it did not add enough height. B was strong because it added more height. They want the platform that helps most. Design B works better than Design A because the data shows 51 inches reached. The extra height helps reach higher, solving the reaching problem. Based on the data, which design works better?

Design A works better because the data shows 48 inches is higher.
Design B works better because the data shows 51 inches, so it helps reach higher. (correct answer)
Design B works better because it is taller and I like it.
Design B works better because it reached 51 inches.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, [problem: reaching high shelves]. Test data showed: Design A [results: reached 48 inches]. Design B [results: reached 51 inches]. The students concluded that Design [B] works better because [specific reasoning from stimulus: the data shows it reached 3 inches higher (51 vs 48), proving extra height helps reach higher shelves]. Choice [B] is correct because it [identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion]. For example, [specific complete reasoning: 'Design B works better because the data shows 51 inches (evidence), which means the taller height (design feature) helps reach higher shelves (solves problem)']. Choice [A] represents [error type: wrong evidence]. This error typically occurs when students [developmental explanation: use wrong numbers]. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 12

In science discussion, Chen and Maya tested two shelves to store books. Design A had 1 shelf and held 8 books. Design B had 3 shelves and held 24 books. Both designs tried to solve the storage problem, but one held more books. Design B's strength is more shelves give more room, and Design A's weakness is less space. Chen said, "We should use the data to decide." Maya pointed to 24 and said, "That is more than 8." The teacher asked, "How do you know which shelf works better?" Based on the data, how do they know Design B works better?

Design B works better because the data shows 24 books, so more shelves give more space for storage. (correct answer)
Design A works better because the data shows 8 books, so it holds more than 24.
Design B works better because it has three shelves, and we do not need data.
Design A works better because I like one shelf better.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem is storing more books. Test data showed: Design A results: held 8 books. Design B results: held 24 books. The students concluded that Design B works better because the data shows it held 16 more books (24 vs 8), proving multiple shelves increase storage capacity. Choice A is correct because it identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion. For example, 'Design B works better because the data shows 24 books (evidence), so more shelves (design feature) give more space for storage (solves problem)'. Choice B represents reversed logic. This error typically occurs when students use wrong numbers. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 13

In the classroom, Marcus and Yuki tested two containers to organize crayons and markers. Design A was one big box, and the items got mixed up (yes). Design B had dividers, and the items stayed separated (yes). Both designs tried to solve the organization problem, but one kept things apart. Design B's strength is dividers separate items, and Design A's weakness is mixing. Yuki said, "The evidence is on our chart." Marcus said, "Let's pick the one that solves the problem better." The teacher asked, "What evidence shows which design works better?" What evidence shows which design works better?

Design B works better because the data says items stayed separated with dividers. (correct answer)
Design A works better because it is one box and looks simple.
Design B works better because I like the word "dividers."
Design A works better because both designs kept items separated.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem is organizing supplies without mixing. Test data showed: Design A results: items got mixed (yes). Design B results: items stayed separated (yes). The students concluded that Design B works better because the data shows items stayed separated, proving the dividers prevent supplies from mixing. Choice A is correct because it identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion. For example, 'Design B is better because test results show items stayed separated (evidence), proving the dividers (design feature) prevent supplies from getting mixed up (solves problem)'. Choice D represents claiming both equal when data shows difference. This error typically occurs when students think all designs are good if they tried to solve problem. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 14

During a science discussion, Jamal and Maya tested two funnels to pour water into a bottle. Design A had a wide opening and spilled 2 tablespoons. Design B had a narrow opening and spilled 5 tablespoons. Both designs tried to solve the pouring problem, but one spilled less. Design A's strength is the wide opening catches more water, and Design B's weakness is it misses and spills more. Maya said, "Less spilled means it works better for pouring." Jamal looked at the data and agreed. The teacher asked, "Which design works better, and what evidence shows it?" Based on the data, which funnel design works better and why?

Design B works better because the data shows 5 tablespoons spilled, so it pours neatly.
Design A works better because the data shows 2 tablespoons spilled, so the wide opening caught more water. (correct answer)
Design A works better because I like wide funnels.
Design A works better because both funnels spilled the same amount.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem is pouring without spilling. Test data showed: Design A results: spilled 2 tablespoons. Design B results: spilled 5 tablespoons. The students concluded that Design A works better because the data shows it spilled 3 tablespoons less (2 vs 5), proving the wide opening catches liquid better. Choice B is correct because it identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion. For example, 'Design A works better because it spilled 3 tablespoons less (evidence), showing the wide opening (design feature) catches liquid better when pouring into bottles (solves problem)'. Choice A represents wrong design selected. This error typically occurs when students select wrong design despite data showing poor performance. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 15

At presentation time, Marcus and Yuki tested two bases to hold up a tall tower. Design A had a narrow base, and it tipped over (yes). Design B had a wide base, and it stayed up (yes). Both designs tried to solve the stability problem, but one worked better. Design B's strength is the wide base helps it stay up, and Design A's weakness is it tips easily. Yuki said, "The evidence tells us which one is safer." Marcus pointed to the word "tipped" on the results sheet. The teacher asked, "How do you know which design works better?" Using the test results, which base design works better and why?

Design A works better because it tipped, so it is stable.
Design B works better because the data shows it stayed up, so the wide base stopped tipping. (correct answer)
Design B works better because it is wider, and wider always looks cooler.
Design B works better because it stayed up, but we do not need it to stay up.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem is preventing container from tipping. Test data showed: Design A results: tipped over (yes). Design B results: stayed standing (yes). The students concluded that Design B works better because the data shows it didn't tip over, proving the wide base provides stability. Choice B is correct because it identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion. For example, 'Design B works better because the data shows it stayed up (evidence), proving the wide base (design feature) stopped tipping (solves problem)'. Choice A represents reversed logic. This error typically occurs when students confusing designs' results. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 16

Emma and Jamal tested trays to carry books. Design A is flat and 2 books fell. Design B has edges and 0 books fell. A tried to help, but no edges was a weakness. B's edges were a strength. They need to pick one tray for carrying books. Design B works better than Design A because the data shows 0 books fell. The edges stopped books from sliding off. This solves the problem of carrying books safely. Based on the data, which design should they choose and why?

Design A works better because 2 books fell, so it is safer.
Design B works better because the data shows 0 fell, so edges stop sliding. (correct answer)
Design B works better because I like trays with edges.
Design B works better because 0 books fell.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, [problem: carrying books without dropping]. Test data showed: Design A [results: 2 of 3 books fell]. Design B [results: 0 of 3 books fell]. The students concluded that Design [B] works better because [specific reasoning from stimulus: the data shows 0 books fell, proving the raised edges successfully prevented books from sliding off]. Choice [B] is correct because it [identifies correct design based on data: chooses design with better performance; provides evidence: cites specific test results; explains reasoning: connects data to design feature to problem solution; makes complete argument: includes all three parts of evidence-based conclusion]. For example, [specific complete reasoning: 'Design B works better because the data shows 0 books fell (evidence), which means the raised edges (design feature) successfully prevented books from sliding off when carrying them (solves problem)']. Choice [C] represents [error type: opinion without evidence]. This error typically occurs when students [developmental explanation: don't use data to decide, pick design they prefer instead of one that performed better]. To help students make evidence-based conclusions: Use three-part frame: 'Design [X] works better because [data evidence] shows that [design feature] [solves problem successfully]'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('A works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 17

Amir and Yuki tested two shelves to store classroom books. Design A had 1 shelf and held 8 books. Design B had 3 shelves and held 24 books. A tried to store books, but it was weak because it held fewer. B was strong because more shelves made more space. Yuki said, "We should pick the one that holds more books." Amir pointed to the data to be sure. They need the best design for the storage problem. What evidence shows which design works better?

Design A works better because 1 shelf is easier to count.
Design B works better because it held 24 books, while Design A held 8. (correct answer)
Design B works better because it is three shelves, and three is my favorite number.
Design A works better because it held 24 books, while Design B held 8.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem was storing more books. Test data showed: Design A (1 shelf) held 8 books. Design B (3 shelves) held 24 books. The students concluded that Design B works better because the data shows it held 16 more books (24 vs 8), proving multiple shelves increase storage capacity. Choice B is correct because it identifies the correct design based on data (Design B held 24 books while Design A held 8), provides specific evidence from the test results, and clearly states which design performed better. The statement 'Design B works better because it held 24 books, while Design A held 8' gives a complete comparison showing B's superior performance. Choice D represents the error of confusing the designs' results by switching which design had which data. This error typically occurs when students mix up the test results, attributing Design A's performance to Design B and vice versa, showing they haven't carefully read the data. To help students make evidence-based conclusions: Use three-part frame: 'Design B works better because 24 books shows that more shelves hold more books'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('three is my favorite number') and evidence-based conclusion ('B works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 18

Carlos and Emma wanted to keep crayons and markers from getting mixed up. They tested Container Design A (one box) and Design B (dividers). The data shows in A the items mixed (yes), and in B the items stayed separated (yes). A tried to organize, but it was weak because everything mixed together. B was strong because the dividers kept items apart. Carlos said, "We should use the one that keeps things separate." Emma pointed to the test results. Using the test results, which design should they choose and why?

Design A works better because the data shows items mixed, so it keeps supplies organized.
Design B works better because the data shows items stayed separated, so dividers stop supplies from mixing. (correct answer)
Design B works better because it has more parts, so it must be better.
Design B works better because it stayed separated, but that is just a guess.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem was organizing supplies without mixing. Test data showed: Design A (one box) had items get mixed (yes). Design B (with dividers) had items stay separated (yes). The students concluded that Design B works better because the data shows items stayed separated, proving the dividers prevent supplies from mixing. Choice B is correct because it identifies the correct design based on data (Design B with better performance), provides evidence (cites specific test results of items staying separated), explains reasoning (connects data to design feature of dividers to problem solution of preventing mixing), and makes a complete argument including all three parts of an evidence-based conclusion. For example, 'Design B works better because test results show items stayed separated (evidence), proving the dividers (design feature) prevent supplies from getting mixed up (solves problem)'. Choice A represents the error of selecting the wrong design despite data showing poor performance and reversed logic. This error typically occurs when students misunderstand what the data means, thinking that 'items mixed' is a positive result rather than a failure to solve the organizing problem. To help students make evidence-based conclusions: Use three-part frame: 'Design B works better because items stayed separated shows that dividers stop supplies from mixing'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('it has more parts') and evidence-based conclusion ('B works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 19

Jamal and Sofia needed to reach a high shelf. They tested Platform Design A (3 inches) and Platform Design B (6 inches). The data shows A helped them reach 48 inches and B helped them reach 51 inches. A tried to help, but it was weak because it gave less height. B was strong because it was taller and helped them reach higher. Sofia said, "Let's use the evidence." Jamal agreed after seeing the numbers. Based on the data, which design should they choose and why?

Design A works better because the data shows 48 inches, so it reaches higher than 51.
Design B works better because the data shows 51 inches, so extra height helps reach the shelf. (correct answer)
Design B works better because it is bigger, and bigger is always best.
Design B works better because it reached 51 inches, but I do not know what that means.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem was reaching high shelves. Test data showed: Design A (3-inch platform) reached 48 inches. Design B (6-inch platform) reached 51 inches. The students concluded that Design B works better because the data shows it reached 3 inches higher (51 vs 48), proving extra height helps reach higher shelves. Choice B is correct because it identifies the correct design based on data (Design B with better performance), provides evidence (cites specific test results of 51 inches), explains reasoning (connects data to design feature of extra height to problem solution of reaching shelves), and makes a complete argument including all three parts of an evidence-based conclusion. For example, 'Design B works better because it reached 51 inches (evidence), showing that the 6-inch height (design feature) helps students reach higher shelves (solves problem)'. Choice A represents the error of selecting the wrong design despite data showing poor performance and confusing which number is higher. This error typically occurs when students misread numbers or don't understand that 51 is greater than 48, leading them to pick the design that actually performed worse. To help students make evidence-based conclusions: Use three-part frame: 'Design B works better because 51 inches shows that extra height helps reach higher'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('bigger is always best') and evidence-based conclusion ('B works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.

Question 20

Sofia, Chen, and Maya tested two storage shelves for a class library. Design A had 1 shelf and held 8 books. Design B had 3 shelves and held 24 books. A tried to store books but had little space, so it was weak. B was strong because it had more shelves for more books. Chen first thought A was fine, but Sofia pointed to the numbers. The teacher asked, "Which design works better? What does the data tell us?" They want the shelf that solves the storage problem best. Based on the test results, which design best solves the problem?

Design B works better because the data shows 24 books, so more shelves hold more books. (correct answer)
Design A works better because the data shows it held 8 books, so it has the most space.
Design B works better because it is taller, and tall things are always better.
Design B works better because it held 24 books, but I do not know why.

Explanation: This question tests the 1st grade skill of using evidence from data to determine which design works better and explaining why (K-2-ETS1-3: Analyze data from tests to compare strengths and weaknesses and determine which design works better). After testing two designs and analyzing the data to find strengths and weaknesses, we use all that evidence to make a conclusion about which design works better for solving the problem. An evidence-based conclusion includes three parts: (1) stating which design works better, (2) providing specific data evidence (test results, numbers, observations), and (3) explaining the reasoning that connects the data to the design's features and to solving the problem. We don't choose based on which design we like, which looks nicer, or which was easier to build - we choose based on which one PERFORMED BETTER according to the test data. The design that works better is the one that solves the problem more successfully, as proven by the evidence from testing. In this scenario, the problem was storing more books. Test data showed: Design A (1 shelf) held 8 books. Design B (3 shelves) held 24 books. The students concluded that Design B works better because the data shows it held 16 more books (24 vs 8), proving multiple shelves increase storage capacity. Choice A is correct because it identifies the correct design based on data (Design B with better performance), provides evidence (cites specific test results of 24 books), explains reasoning (connects data to design feature of more shelves to problem solution of storing more books), and makes a complete argument including all three parts of an evidence-based conclusion. For example, 'Design B works better because the data shows it held 24 books (evidence), proving that multiple shelves (design feature) increase storage capacity for the class library (solves problem)'. Choice B represents the error of selecting the wrong design despite data showing poor performance and confusing the designs' results. This error typically occurs when students misread which design had which results or think the smaller number is better without understanding the problem requires storing MORE books. To help students make evidence-based conclusions: Use three-part frame: 'Design B works better because 24 books shows that more shelves hold more books'; practice complete reasoning chains (data → what it means → how design causes that → why that solves problem); emphasize difference between opinion ('I like A better') and evidence-based conclusion ('B works better because data shows...'); review data and strengths/weaknesses before concluding; ask guiding questions: 'Which design had better results?' 'What data tells you that?' 'Which design feature caused those good results?' 'How does that solve the problem?'. Watch for: students choosing based on preference not data, stating conclusion without reasoning, using data but not connecting to why that matters, selecting wrong design despite data showing poor performance, thinking if a design works at all it's 'good enough' without comparing to see which works BETTER, or providing partial reasoning that's missing key connections. Key concept: Data-driven decision making = using test results to choose the design that solves the problem best, and explaining your reasoning with evidence.